Operations | Monitoring | ITSM | DevOps | Cloud

Fully taking advantage of cloud infrastructure includes the ability to scale up and down dynamically, taking the need and load off your services. The compute services like Amazon Web Services (AWS) EC2, Azure Virtual Machines (VM), and Google Cloud Platform (GCP) Compute Engine allow Auto Scaling of the instances of the service. This helps manage the responsiveness and costs of your cloud services by ensuring that the instance counts go up and down depending on demand.

When first looking into serverless migration and its architecture, it can feel like you’re staring down an endless shopping aisle of critical serverless tools that all need to be put into your basket straight away. Some services seem to offer the same function, while others can feel wildly different - both, as a result, can instill some doubts as to what is really necessary for your business and serverless application.

From the Cloud First policy established in 2010 to last year’s Cloud Smart update, it’s clear the government is driving federal agencies toward cloud computing. The strategy makes sense, but for agencies migrating, however, the decision is less clear cut, because there are several options agencies can choose based on individual agency needs.

At Lumigo, we recently ran into some issues with a service we built on top of our Nodejs AWS Lambda handler. These issues were the result of lambda execution leaks from within our serverless code. In this article, I’ll explain about node.js lambda execution leaks and how to avoid them.

A while ago, we covered the invocation (trigger) methods supported by Lambda and the integrations available with the AWS catalog. Now we’re launching a series of articles to correlate these integration possibilities with common serverless architectural patterns (covered by this literature review). In Part I, we will cover the Orchestration & Aggregation category. Subscribe to our newsletter and stay tuned for the next parts of the series.

This was originally posted on The New Stack. Once upon a time, log management was relatively straightforward. The volume, types, and structures of logs were simple and manageable. However, over the past few years, all of this simplicity has gone out the window. Thanks to the shift toward cloud native technologies—such as loosely coupled services, microservices architectures, and technologies like containers and Kubernetes—the log management strategies of the past no longer suffice.

It’s a day for celebration! Our migration is complete, and our applications are now running in the cloud environment best suited to their needs. The rest of our application inventory, the ones not cut out for the cloud, remain on-premises where they belong. Actually…we’re not done yet. We still have some work to do to make sure our hybrid environment runs smoothly and delivers the business value we expect. Fortunately, we aren’t the first ones to travel this path.